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Machine Learning and Knowledge Discovery in Databases
Cellier, Peggy [ed.]
;
Driessens, Kurt [ed.]
English Conference proceedings (Book) Scientific
Published: Springer Netherlands, Cham, Switzerland
2020
Series:
Communications in Computer and Information Science 1865-0929 1865-0937, 1167
Identifiers
MTMT: 31264621
DOI:
10.1007/978-3-030-43823-4
ISBN:
9783030438234
ISBN:
9783030438227
Other URL:
http://link.springer.com/10.1007/978-3-030-43823-4
Chapters
Bräm Timo et al. Attentive Multi-task Deep Reinforcement Learning. (2020) In: Machine Learning and Knowledge Discovery in Databases pp. 134-149
Scholbeck C.A. et al. Sampling, Intervention, prediction, aggregation: A generalized framework for model-agnostic interpretations. (2020) In: Machine Learning and Knowledge Discovery in Databases pp. 205-216
Hegedűs István et al. Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning. (2020) In: Machine Learning and Knowledge Discovery in Databases pp. 317-332
Muecke Sascha et al. Hardware Acceleration of Machine Learning Beyond Linear Algebra. (2020) In: Machine Learning and Knowledge Discovery in Databases pp. 342-347
Boudebza S. et al. Detecting stable communities in link streams at multiple temporal scales. (2020) In: Machine Learning and Knowledge Discovery in Databases pp. 353-367
Coppens L. et al. A comparative study of community detection techniques for large evolving graphs. (2020) In: Machine Learning and Knowledge Discovery in Databases pp. 368-384
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2025-05-05 23:40
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